This book provides a comprehensive guided tour to the users for performing remote sensing and GIS operations in free and open source software i.e. R. This book is suitable for the users who have basic knowledge of remote sensing and GIS, but no or little knowledge about R software. It introduces the R software to users along with the procedures for its downloading and installation. It provides R-codes for loading and plotting of both raster and vector data; pre-processing, filtering, enhancement and transformations of raster data; processing of vector data; unsupervised and supervised classification of raster data; and thematic mapping of both raster and vector data. In addition to it, this book provides R-codes for performing advanced machine learning algorithms like random forest, support vector machine, etc. for supervised classification of raster data. This book is apt for the users who don’t have access to the sophisticated paid software of GIS and digital image processing. Sample data for practice is provided in an additional DVD so that users can get hands on training of the R-codes given in this book. This book can serve as a training manual for performing digital image analysis and GIS operations in R software.

Alka Rani, Scientist,  ICAR – Indian Institute of Soil Science, Madhya Pradesh, India

Nirmal Kumar, Scientist, ICAR – National Bureau of Soil Survey and Land Use Planning, Maharashtra, India

S.K. Singh, Director, ICAR – National Bureau of Soil Survey and Land Use Planning, Maharashtra, India

N.K. Sinha, Scientist, ICAR – Indian Institute of Soil Science, Madhya Pradesh, India

R.K. Jena, Scientist, ICAR – National Bureau of Soil Survey and Land Use Planning, Assam, India

Himesh Patra, Scientist (Geoinformatics), Crop Data Technology Private Limited, Maharashtra, India

1. Download and Installation of R 2. Data availability and downloading 3. Raster data in R
4. Radiometric Calibration 5. Vector data in R 6. Coordinate Reference Systems (CRS) in R
7. Subset Raster 8. Vector Data Analysis 9. Mosaic Raster Images 10. Resampling of Raster Images 11. Raster data statistics 12. Image Contrast Enhancement 13. Spatial Filters 14. Transformations 15. Unsupervised Classification 16. Supervised Classification 17. Digital terrain analysis 18. Thematic mapping